Sensory experience that individuals perceive during the use and wear of garments

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Score Sheet - Textile Evaluation Nov 2023 (clone) Feb 2024 PCA workbook (4)Twenty-seven (k=27) ready-to-wear clothing textiles were sourced from Metro, a large textile store in Pretoria, South Africa, by XXX (with experience as a clothing buyer at a major clothing retailer). Textiles, coloured and patterned, were chosen based on their widespread popularity and frequent use as ready-to-wear textiles in everyday clothing (based on the researchers’ expertise). Calico was chosen as a reference textile due to its well-documented properties (Kadolph, 2014) and its undyed and unfinished nature, making it a suitable standard for comparison.Textiles were cut to measure 20 cm x 20 cm samples. The mass (g) (Mettler Toledo electronic precision scale) of textile sample circles (10cm diameter), cut using a James H. Heal sample cutter (Model 230/140), was measured and converted to g/m². The samples were conditioned for a minimum of 24 hours in standard atmospheric conditions (20 ± 2°C temperature and 65 ± 2% relative humidity) and labelled using a numerical code as recommended by Nagamatsu et al. (2018) and SüLar and Okur (2007). Samples were presented to panellists unlaundered.Senior university students with clothing and textiles as major subjects were recruited as panellists for both phases. Panellists with appropriate experience are often selected due to their expertise and ability to discriminate and describe products (Irie et al., 2018; SüLar & Okur, 2007). The panellists (Phase 1; n=28 and Phase 2; n=13) received training on hand evaluation of textiles. The training, conducted in a classroom setting, was based on the methods described by other textile researchers (Luible et al., 2007; Nagamatsu et al., 2018; SüLar & Okur, 2007). Participants were given a textile sample (Calico) and trained to evaluate textiles using their hands, palms, and fingertips. Samples were squeezed between thumbs and index fingers, held and moved back and forth between thumbs and fingers. Panellists were also required to run their fingers over the textile sample.Panellists (n = 28), seated in a classroom format, developed descriptors for tactile attributes of the 27 textile samples during two 1.5 h sessions. The panellists were handed a transparent bag containing the 27 textile samples. Removing one textile sample at a time, panellists had to evaluate each sample and write down terms describing its tactile attributes (based on prior experience).Panellists generated a list of terms individually to ensure efficient discussion (Irie et al., 2018). Evaluation was limited to 5 minutes per sample with a 1-minute break between samples to limit panellist fatigue.An initial list of 99 terms was generated by panellists. The researcher eliminated duplicate, multi-dimensional and hedonic terms. During a 1-hour discussion, synonyms of all descriptors were identified (e.g. elastic, elasticity) as recommended by Drake and Civille (2003), Irie et al. (2018) and Lawless and Civille (2013). Terms were linked and combined to reduce the number of terms, and terms in continuous tense were removed (e.g. flowing) (first reduction). During an additional 1-hour discussion (second reduction), terms describing other sensorial parameters were eliminated (e.g. audible). The researcher continued to reduce the list by creating overarching terms to represent the remaining terms (e.g. even, flat and uniform became sleek).Afterwards, the researcher reorganized the terms into a rational list (third reduction), and the panel defined each term by consensus. As recommended by (ASTM E253-20:2020), each term in the final list was clearly defined with input from panellists and literature related to the development of lexicons. Due to the limited number of published lexicons for clothing textiles, lexicons for cosmetics and food products were consulted to generate suitable definitions. A descriptive clothing textile tactile attribute (DCTTA) lexicon with 17 descriptors was developed.After the training, panellists were asked to wash their hands with non-moisturizing soap (Nature’s Nourishment, CJ Distribution) and fully dry them with hot air. The descriptive hand evaluation was done in a sensory laboratory (ISO 8589:2007). The laboratory was prepared to mimic standard atmospheric conditions (20 ± 2°C temperature and 65 ± 2% relative humidity) (Nagamatsu et al., 2018; SüLar & Okur, 2007). Panellists were seated in individual cubicles, each having a non-metallic surface, allowing for low thermal absorption, as recommended by Musa et al. (2019). Red-coloured lights were switched on at a low intensity before the start of the evaluation to mask visual colour differences between samples (Meilgaard et al., 2007). The same 27 labelled textile samples were evaluated with reference to Calico. The samples were presented in a transparent plastic bag to each panellist. Panellists evaluated the samples in random order. Responses were entered directly into Compusense® 2.0. Each sample was evaluated only once to avoid excessive handling and possibly initiating alteration of tactile properties.Line scales anchored with verbal descriptors were employed to measure the intensities of the different attributes of each textile sample, with zero indicative of the absence of the attribute measured and 10 indicative of a high intensity of the attribute, similar to the study by Harpa et al. (2018). A 10-minute break after the evaluation of the first 13 samples was implemented to avoid fatigue. The assessment was limited to 5 minutes per sample.Two-way analysis of variance with panellists and textiles as factors was applied to the sensory data. Where textile differences (p < 0.05) were noted, Tukey’s honestly significant difference (HSD) test was applied to separate means. Principal Component Analysis (PCA) employing attribute means across panellists for the 27 samples was used to summarise the multivariate data. This analysis assisted in simplifying the interpretation by reducing the data dimensions and understanding the variation among textile samples. Sock Evaluation - Raw data exportThe study utilised an established lexicon developed by the researchers (XXX and XXX) for implementation in the descriptive hand evaluation procedure. The lexicon, previously developed for everyday wear textiles, was selected because it is specifically relevant for evaluating the tactile properties of fabrics for ready-to-wear garments (e.g., socks) and provides a consistent reference point for describing and comparing other textiles. The original lexicon comprised 17 textile tactile descriptors, namely: bounciness, breathability, flowiness, hairiness, hardness, irregularity, rigidity, roughness, scratchiness, smoothness, stickiness, stretchy, synthetic nature, thermal sensation, thickness, weight, and wrinkledness. For the purposes of the present study, since panellists had to evaluate the technical face and back twice, it was decided to limit the number of descriptors to only the essential ones to avoid panellist fatigue. Each attribute’s relevance to knits, sock fabrics, and fabric hand was carefully studied. The selected attributes are hairiness, scratchiness, irregularity, roughness, synthetic nature, thermal sensation, thickness, and weight. Other attributes were excluded because they were considered redundant or not influential on the hand feel of socks in everyday wear.The final lexicon (n=8 attributes) was used to rate the perceived intensities of the descriptors for each sample, for both the technical face and the technical back of the sock fabrics.Ten different socks, including both boys’ and girls’ socks, were obtained from six major retailers and manufacturers in South Africa for the study. The selection represented the overall market offering, including the most common structural and aesthetic properties of socks, i.e., striped, dotted, cartoon character, lurex, textural designs, tie-dye, checkered, ribbed, plain and cushioned. This sample number aligns

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